Geophysical Imaging and Monitoring
Andrea Balza Morales
M.Sc.
Andrea Balza Morales
PhD researcherM.Sc. Andrea Balza Morales
Geophysical Imaging and Monitoring
RWTH Aachen University
Wüllnerstr. 2 (Bergbaugebäude)
Room: 505d
52062 Aachen
Research Interests
- Gravity and magnetic data processing and inversion
- Time-lapse monitoring techniques
- Structure-based inversion
- 3D Geological modeling
- Geothermal exploration using joint interpretation and inversion
Professional experience
| 2021 – present | PhD Researcher at RWTH Aachen and ETH Zürich within the MSCA Action EASYGO |
| 2013 – 2021 | Geophysical Data Processor at EDCON-PRJ Inc (Denver, Colorado) |
| 2016 – 2017 | Graduate Research Assistant at Colorado School of Mines (Golden, Colorado) |
Education
| 2014 – 2017 | Masters of Geophysics (M.Sc.) at Colorado School of Mines (Golden, Colorado) |
| 2012 – 2013 | International Exchange Program at University of New Mexico (Albuquerque, New Mexico) |
| 2008 – 2013 | Geophysical Engineering (B.Sc.) at Universidad Simon Bolivar (Caracas, Venezuela) |
Awards and service to profession
| 2012 – 2013 | Mendenhall Prize for Outstanding Graduating Master of Science Students, Department of Geophysics, Colorado School of Mines. Denver, Colorado |
| 2004 – 2005 | All-American Scholar award, United States Achievement Academy. Miami, Florida |
| 2020 – 2022 | Serving Chair, Geophysical Society of Houston, Potential Field Special Interest Group |
| 2021 | Membership Committee, EEGS, Environmental and Engineering Geophysical Society |
| 2020 – 2021 | Coding Group Leader, GeoLatinas - Latinas in Earth and Planetary Sciences |
Publications
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Electrical resistivity monitoring of CO2 injection at the Mont Terri underground laboratory, Switzerland
2025 |
Journal of Applied Geophysics, doi:10.1016/j.jappgeo.2025.105852
RWTH Publications PDFAbstract
Monitoring CO2 injection in the subsurface using geophysical methods, particularly in caprocks or hard rock, presents unique challenges. These challenges arise due to the lower porosity and permeability in hard rock settings, which result in limited and complex pathways for fluid movement. The Mont Terri underground rock laboratory in Switzerland provides the opportunity to evaluate different geophysical measurements in boreholes to monitor a CO2 injection near a known fault zone. The motivation of the experiment presented in this study, along with its continuation in the Carbon Sequestration series D and E (CS-D and CS-E) is to assess the integrity of a fault zone within a caprock-like formation (such as Opalinus Clay) during long-term leakage experiment. Time-lapse electrical resistivity tomography (ERT) measurements were conducted during the steady-state injection period. In this work we present an ERT study using synthetic data to predict the effects of both the conductive fault zone and the injected fluid mixture at a single time step, while also analyzing the temporal evolution of the synthetic study. The synthetic results show a similar apparent resistivity distribution to that observed in the field data. The analysis then progressed to real field data, where various electrode configurations were tested, requiring meticulous assessment of data quality during processing. This study highlights the importance of using appropriate error estimation techniques, such as a reciprocal error model, to characterize the spatial and temporal behavior of measurement errors across different configurations. Three-dimensional time-lapse inversion results play a crucial role in deciphering the fluid interaction between the injected CO2, the properties of the host rock, and the presence of the main fault zone within the experiment. Our findings indicate that the fracture network within the host rock is intricate, exhibiting changes in resistivity during injection around the main fault zone. These insights not only complement other findings within the CS-D and CS-E experiments, but also showcase the utility of ERT measurements in CO2 monitoring within other hard rock settings.
Cite as
Balza-Morales, A. and Grab, M. and Rinaldi, A. P. and Zappone, A. and Maurer, H. and Wagner, F. M. (2025): Electrical resistivity monitoring of CO2 injection at the Mont Terri underground laboratory, Switzerland. Journal of Applied Geophysics. https://doi.org/10.1016/j.jappgeo.2025.105852
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Integrative analysis of the Aachen geothermal system (Germany) with an interdisciplinary conceptual model
2025 |
Geothermal Energy, doi:10.1186/s40517-024-00327-0
PDFAbstract
The comprehension of geothermal systems involves the efficient integration of geo‑logical, geophysical and geochemical tools that are crucial in unraveling the distinct features inherent in geothermal reservoirs. We provide a first approach to compre‑hending the geologically complex geothermal system in the Aachen area, which has been known for its natural thermal spring occurrences since Roman times. Through a comprehensive analysis involving geochemical interpretation of water samples, a review of 2D seismic profiles, stress analysis, and surface geology, a dynamic model has been built, which serves as a conceptual framework providing a clearer under‑standing of the system. The model characterizes a non-magmatic, detachment faultcontrolled convective thermal system, wherein the reservoir exhibits mixed properties of the mainly Devonian carbonate rocks. NW–SE directed fault lines play a pivotal role in fluid transport, enabling the ascent of thermal waters without the need for addi‑tional energy. We additionally conducted magnetotelluric (MT) surveys and analyzed apparent resistivity and impedance values obtained through forward modeling, along with an assessment of noise levels. These findings contribute to evaluating the potential use of MT methods in further evaluating the study area and for geother‑mal energy exploration in general.
Cite as
Gómez-Díaz, E. and Balza Morales, A. and Kukla, P. A. and Brehme, M. (2025): Integrative analysis of the Aachen geothermal system (Germany) with an interdisciplinary conceptual model. Geothermal Energy. https://doi.org/10.1186/s40517-024-00327-0
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Integrating time-lapse gravity, production, and geological structure data in a gas reservoir study
2020 |
Interpretation, doi:10.1190/int-2019-0272.1
Note: This publication resulted from Andrea's master thesis i.e. was prepared before GIM was founded.Abstract
Time-lapse gravity is most commonly used to monitor fluid movement and is especially useful when monitoring water encroachment in a gas reservoir. Although time-lapse gravity data are directly sensitive to the fluid saturation changes in reservoirs, it is still necessary to integrate multiple types of data with complementary information to enhance the time-lapse gravity interpretation. When monitoring water-influx in a reservoir, the changes in water yield in production wells may directly indicate saturation changes with time and provide such complementary information about the areas of fluid movement. We present a workflow to invert a time-lapse gravity data set and production data to help monitor the edge water encroachment through a case study at the Sebei gas field in Western China. Three time-lapse gravity surveys were acquired between 2011 and 2013 and production data were also collected from 286 wells during the same period of time. We integrate the two data sets and the structural information in the reservoir through a framework of constrained time-lapse gravity inversion. In this workflow, we incorporate the information from the production data into the inversion by converting the gas and water yield into a reference model. We also incorporate geological structural information through spatially varying bound constraints. Through this approach, we construct a set of time-lapse density contrast models that are consistent with the time-lapse gravity data, production data, and structural information. The resultant density contrast models better delineate the regions of the reservoir with increased water influx and also enable us to produce improved porosity estimations in the reservoir.
Cite as
Balza Morales, A. and Li, Y. (2020): Integrating time-lapse gravity, production, and geological structure data in a gas reservoir study. Interpretation. https://doi.org/10.1190/int-2019-0272.1
Conference contributions
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Surrogate-assisted Bayesian inference with ERT data for contaminant transport modelling in the subsurface
2025 |
EGU General Assembly, Vienna, 27 April - 2 May 2025
Conference websiteAbstract
Understanding and predicting groundwater contaminant transport is inherently challenging due to uncertainties in both field-specific properties and contaminant-related parameters. These uncertainties pose challenges for effective environmental management, including project planning, non-invasive long-term monitoring, and remediation efforts. To address this, we propose a framework that combines geophysical monitoring, surrogate-assisted Bayesian inference, and dimensionality reduction techniques to quantify and reduce these uncertainties and aid in decision making processes. For the implementation of Bayesian inference, our work focuses on electrical resistivity tomography, a geophysical method that is particularly well-suited for the abovementioned purpose due to its sensitivity to variations in fluid content and temperature. The proposed approach addresses two major computational challenges. First, Bayesian inference requires extensive model runs, which can become computationally prohibitive for large domains with fine grids, multiple processes, and multiple time steps. To mitigate this, we use surrogate models that approximate the full physics-based model using input-output data pairs, significantly reducing computational costs. Second, the high-dimensional nature of ERT data complicates both surrogate training and Bayesian inference. High output dimensions lead to increased training times, larger data requirements, and difficulties in likelihood estimation due to the "curse of dimensionality." To overcome this, we incorporate dimension reduction techniques into the framework. Our main focus is to evaluate how surrogate modeling approximations and dimension reduction strategies influence the accuracy and efficiency of Bayesian inference when using ERT measurements for contaminant transport applications. We apply our framework on a 2D synthetic non-reactive contaminant transport scenario, integrating ERT measurements while accounting for uncertainties in both field-specific and contaminant-related parameters. This methodology provides a practical tool for subsurface engineering, offering improvements in planning, parameter estimation, and long-term monitoring to enhance contaminant transport predictions and remediation strategies.
Cite as
Morales Oreamuno, Maria Fernanda and Menzel, Nino and Oladyshkin, Sergey and Wagner, Florian M. and Nowak, Wolfgang (2025): Surrogate-assisted Bayesian inference with ERT data for contaminant transport modelling in the subsurface. EGU General Assembly, Vienna, 27 April - 2 May 2025. https://doi.org/10.5194/egusphere-egu25-12561
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Integrating geophysical structure-based inversion with implicit geological modeling
2025 |
85. Jahrestagung der Deutschen Geophysikalischen Gesellschaft, 24.-27. Februar, Bochum
Conference websiteNote: This contribution was awarded with the Best Presentation Award at the DGG 2025 conference.Abstract
Interpreting geophysical inversion results across diverse applications presents challenges, particularly when the resulting images from conventional smoothness-constrained inversions lack clear, distinct interfaces. The inclusion of prior information to guide the inversion process adds complexity, especially when those prior data carry their own uncertainties. This study explores methods to improve the representation of geological structures by integrating geophysical data with geological models. While current methods are typically either data-driven or model-driven, they often fail to fully leverage available data in a dynamic, unified geophysical model. We propose a novel framework that integrates geological models and geophysical data through structure-based inversion, which maintains geological realism while improving the imaging of sharp contrasts in geophysical models. To address uncertainties in both the geometric structure and physical parameters, we implement a sequential inversion process. The first step resolves shifts in geological interfaces, and the second step inverts for geophysical parameters, using the updated geometry as a constraint. The approach is implemented using open-source software frameworks, ensuring flexibility and adaptability to a wide range of geophysical scenarios. We demonstrate the efficacy of our approach through synthetic cross-hole travel-time tomography examples and a field case study. Results show that our method successfully recovers subsurface interface geometries from geophysical data confirmed by interpolated borehole data. Furthermore, the method preserves layer heterogeneity, improving interpretability compared to other structure-based inversion approaches with constant layer properties. We anticipate that this method will be applicable to large-scale geophysical surveys and can be extended to a variety of scenarios and geophysical techniques.
Cite as
Balza Morales, A. and Forderer, A. and Wellmann, F. and Wagner F.M. (2025): Integrating geophysical structure-based inversion with implicit geological modeling. 85. Jahrestagung der Deutschen Geophysikalischen Gesellschaft, 24.-27. Februar, Bochum.
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The site selection data hub: a data-centric approach for integrated simulation workflow management in radioactive waste disposal site selection
2024 |
EGU General Assembly, Vienna, 14-19 April 2024
Conference websiteAbstract
Given the importance of ensuring the safe disposal of radioactive waste, it is vital to understand the targeted subsurface systems and to build physics-based models to predict their dynamic responses to human interventions. Constructing robust predictive models, however, is very challenging due to the systems' complexity as well as the scarcity and cost of geophysical data acquisition. Optimal matching of data acquisition and predictive simulations is therefore necessary and can be achieved via integrating predictive process modeling, Bayesian parameter estimation, and optimal experimental design into a modular workflow. This allows to quantify the information content of measurement data and therefore enables optimal planning of data acquisition and monitoring strategies. Conducting such data-integrated simulation studies, however, requires a robust workflow management that ensures reproducibility, error management, and transparency. To meet this demand, we established a data-centric approach to workflow control combining error-managed simulations with a functional data hub, providing simulations with direct access to a database of essential material properties. The latter are being made available as site specific scenario compilations along with uncertainty margins and meta information. The data hub serves as an interface facilitating seamless data and simulation exchange to support subsequent model-driven decision-making processes and guarantees that simulations are conducted using manageable, comparable, and reproducible test cases. Furthermore, it ensures that the simulation results can be readily transferred to a designated repository allowing for real-time updates of the model. The implementation of the data hub is based on a Python-based framework for two different use cases: 1) GUI-based use case: The graphical user interface (GUI) facilitates data import, export, and visualization, featuring distinct sections for geographic data representation, structured table organization, and comprehensive visualization of physical properties in varying dimensions. 2) Module-based use case: Built on the YAML-based data-hub framework, it enables direct integration of simulation modules storing measurements and model parameters in the YAML data format. The data is systematically organized to furnish a versatile data selection framework that allows information to be extracted from a variety of references, including specific on-site measurements, laboratory measurements and other references, thereby enabling a comprehensive exploration of different reference-oriented scenarios. This study showcases the data hub as a management infrastructure for executing a modular workflow. Multiple models—such as process and impact models as well as their surrogates and geophysical inverse models—are generated within this workflow utilizing scenarios provided by the data hub. Our study shows that adopting a data-centric approach to control the simulation workflow proves the feasibility of conducting different data-integrated simulations and enhances the interchangeability of information across different stages within the workflow. The paradigm of sustainable model development ensures reproducibility and transparency of our results, while also offering the possibility of synergetic exchange with other research areas.
Cite as
Chen, Q. and Boxberg, M. S. and Menzel, N. and Morales Oreamuno, M. F. and Nowak, W. and Oladyshkin, S. and Wagner, F. M. and and Kowalski, J (2024): The site selection data hub: a data-centric approach for integrated simulation workflow management in radioactive waste disposal site selection. EGU General Assembly, Vienna, 14-19 April 2024.
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Ein Exponat zur Veranschaulichung von seismischen Wellen für die Öffentlichkeitsarbeit
2024 |
84. Jahrestagung der Deutschen Geophysikalischen Gesellschaft, 10.-14. März, Jena
Conference websiteNote: This conference contribution resulted from a hands-on geophysical experiment at the RWTH science night in November 2023.Abstract
Die Vorführung von seismischen Experimenten in Innenräumen für die Öffentlichkeitsarbeit ist oftmals nicht direkt möglich. Idealisierungen oder Miniaturisierungen sind in solchen Fällen erforderlich. Daher haben wir ein Exponat zur Veranschaulichung von seismischen Wellen in Tischgröße konzipiert. Mit unterschiedlich schweren und großen Fallgewichten, die von einem Gestell aus verschiedenen Höhen fallen gelassen werden, können seismische Wellen erzeugt und mit einem RaspberryShake aufgezeichnet werden. Es wurden verschiedene Materialien (Sand, Schaumstoff und Styropor) verwendet, um deren Einfluss auf die Wellenform zu illustrieren. Für die Aufzeichnung und Visualisierung wurde eine Webapplikation entwickelt, welche die Daten des RaspberryShakes kontinuierlich anzeigte. Dazu wurde über einen STA-LTA-Trigger eine Aufzeichnungsmöglichkeit implementiert, so dass verschiedene Seismogramme verglichen werden konnten. Darüber hinaus wurden Gamification-Elemente eingebaut. So konnten Teilnehmer versuchen vorab aufgezeichnete Seismogramme zu reproduzieren. Außerdem konnten, ähnlich wie bei der Jahrmarktattraktion Hau den Lukas, Signale einer bestimmten Stärke erzeugt werden. Hier sollte dann aber nicht eine möglichst starke Amplitude erzeugt werden, sondern eine vorgegebene Amplitude möglichst genau getroffen werden. Ergänzend wurden noch didaktisch aufbereitete Materialien zur Erklärung von aktiver Seismik und der Untergrunderkundung geliefert. Das Exponat wurde bereits erfolgreich auf der RWTH-Wissenschaftsnacht 5 vor 12 im Herbst 2023 eingesetzt und wird stetig weiterentwickelt.
Cite as
Boxberg, M. S. and van Meulebrouck, J. and Balza Morales, A. and Menzel, N. and Wagner, F. M. (2024): Ein Exponat zur Veranschaulichung von seismischen Wellen für die Öffentlichkeitsarbeit. 84. Jahrestagung der Deutschen Geophysikalischen Gesellschaft, 10.-14. März, Jena.
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Geothermal potential in the Rhine-Ruhr region - Integration of structural analysis and a preliminary magnetotelluric feasibility study
2022 |
European Geothermal Congress, Berlin, 17.-21. Oct. 2022
Abstract
Geothermal systems often occur in geologically complex structural environments with many closely spaced and intersecting faults. These commonly control the associated fluid flow needed for conventional geothermal reservoirs. One of the goals of the Innovative Training Network EASYGO - Efficiency and Safety in Geothermal Operations, aims to better characterize these systems in order to provide an initial assessment of geothermal potential in Europe. The Rhine-Ruhr region was selected as an area of interest for geothermal energy use in the context of the energy and heat transformation change in former coal mining areas. Here, Devonian carbonates and sandstones could play a role as potential reservoirs associated with karst systems or/and fracture zones. The magnetotelluric method has proven to be a useful tool in geothermal plays, where conductive bodies exist at depth. The goal of this study is to identify the structures and associated areas with enhanced fluid flow using structural analysis and magnetotelluric (MT) data. The initial areas chosen in the Rhine-Ruhr region were Rheindahlen, Lüdenscheid, and Aachen. Their local geology confirms favorable conditions for geothermal reservoir development. Additionally, these zones are strategic for MT data acquisition because of their distance from potential sources of anthropogenic noise. The study focuses on a quantitative method for fracture analysis attributes of potential reservoir rocks along with the integration of the geology, fault response modeling, and stress analysis. In addition, we plan to carry out an MT survey integrating the three areas of interest using prior geologic information. For this, we conducted a 3D forward modeling study to simulate the expected MT signals based on the initial structural analysis of the areas of interest. This was done as a feasibility study to predict if the calculated MT signal will be of sufficient signal-to-noise ratio to carefully design future MT acquisition campaigns. Results show favorable structural settings for the transport of fluids (e.g., fault intersection), where the structural component is marked by NW-SE striking normal faults and NE-SW oriented thrust faults with a strike slip-dilation component. Preliminary fracture analysis observed on the surface supports hints of density fracture zones for water circulation, but further studies should be conducted to see if these fractures propagate at depth. The synthetic MT study shows that a considerable signal is expected from conductive bodies within the range of 3,500 to 4,000 m depth. The characterization of the reservoir potential in these areas will facilitate similar studies in the entire Rhine-Ruhr region for a better understanding of the geothermal potential of North Rhine-Westphalia. This project has received funding from the European Unions Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie grant agreement No 956965.
Cite as
Balza Morales, A. and Gomez Diaz, E. and Brehme, M. and Kukla P. A. and Wagner, F. M. (2022): Geothermal potential in the Rhine-Ruhr region - Integration of structural analysis and a preliminary magnetotelluric feasibility study. European Geothermal Congress, Berlin, 17.-21. Oct. 2022.
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Towards structure-based joint geological-geophysical inversion for improved characterization of geothermal reservoirs
2022 |
EGU General Assembly 2022, Vienna, Austria, 23-27 May 2022
Conference websiteAbstract
Proper characterization of geologic structures that host geothermal systems is crucial for the efficiency and safety of their energy production. This includes estimating layer boundaries, complex geologic features, and lithology through means of inversion and its regularization. However, existing advanced regularization techniques (e.g., geostatistical regularization, minimum-gradient support, etc.) fail to capture the complexity of 3D geological models including fault networks, fault-surface interactions, unconformities, and dome structures. Förderer et al (2021) propose a solution by means of structure-based inversion, which implements implicit geological modeling and low-dimensional parametrization to produce sharp subsurface interfaces in 2D. This work aims to extend their approach to image realistic and complex geometries in 3D. We continue with the example of electrical resistivity tomography (ERT) and synthetic data; however, this approach is aimed towards independent and joint inversion of geophysical methods that are commonly used in geothermal exploration such as magnetotellurics, gravity, and seismic techniques. The 3D geological model is created using GemPy, an open-source Python library, which constructs a structural geological model from interface points and orientations using an implicit approach based on co-kriging (de la Varga et al., 2019). Subsequently, the 3D model is discretized, and physical parameters are assigned using minimal pilot points that are then interpolated. We use pyGIMLi (Rücker et al., 2017), another open-source multi-method library for geophysical modelling and inversion, to perform a structure-based inversion, where we include the interface points in the primary model vector of the inversion to update these points iteratively to estimate a geological model in agreement with the geophysical observations. In this work, special focus is placed on the sensitivity of each model parameter. To maintain low parametrization and account for the increase in computational power, the cumulative sensitivity is calculated and tested under criteria to optimize the model updates. This is relevant for geometries where the interface and pilot points are more influential in one dimension than others. The workflow has also been adapted to include more complex structures that can be defined in 3D, especially those that reflect geothermal systems. This work is part of the Innovative Training Network EASYGO (www.easygo-itn.eu), which aims to improve the efficiency and safety of geothermal operations but can be readily used in other applications. References: Förderer, A., Wellmann, F., and Wagner, F.M.: Geoelectrical imaging of subsurface discontinuities and heterogeneities using low-dimensional parameterizations, EGU General Assembly 2021, online, 19-30 Apr 2021, EGU21-10012, https//doi.org/10.5194/egusphere-egu21-10012, 2021. de la Varga, M., Schaaf, A., and Wellmann, F., 2019. GemPy 1.0: open-source stochastic geological modeling and inversion, Geosci. Model Dev., 12, 1-32, doi 10.5194/gmd-12-1-2019. Rücker, C., Günther, T., Wagner, F.M., 2017. pyGIMLi: An open-source library for modelling and inversion in geophysics, Computers and Geosciences, 109, 106-123, doi 10.1016/j.cageo.2017.07.011.
Cite as
Balza Morales, A. and Gomez Diaz, E. and Brehme, M. and Kukla P. A. and Wagner, F. M. (2022): Towards structure-based joint geological-geophysical inversion for improved characterization of geothermal reservoirs. EGU General Assembly 2022, Vienna, Austria, 23-27 May 2022.